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In order to implement #95, we need to have access to all info about matcher params and metric params along with the eventual metric output and any other metadata needed to have a complete record of what was done.
We should implement a Result object that is returned from Metric.compute() with the follwing info:
Matcher info: a dictionary containing the matcher name and any parameters, e.g. {”name”: IOU Matcher, “threshold”: 0.5}
Metrics info with name and parameters, similar to matcher
Results (generic dictionary with whatever the metric wants)
Traccuracy version (tag and commit)
Other metadata to help users identify which run their results are from, including the "name" of the solution and gt TrackingGraph (this would require also letting users provide a name for their TrackingGraph), or date/time of run
We need the Matcher info to also be stored in the Matched object for continuity of information.
Then #95 is simply a to_dict and/or to_file function in this class. run_metrics can call that automatically with a user-provided or default location with one metric for file or all metrics in one file. Details TBD 🙂
The text was updated successfully, but these errors were encountered:
In order to implement #95, we need to have access to all info about matcher params and metric params along with the eventual metric output and any other metadata needed to have a complete record of what was done.
We should implement a Result object that is returned from
Metric.compute()
with the follwing info:{”name”: IOU Matcher, “threshold”: 0.5}
We need the Matcher info to also be stored in the Matched object for continuity of information.
Then #95 is simply a to_dict and/or to_file function in this class.
run_metrics
can call that automatically with a user-provided or default location with one metric for file or all metrics in one file. Details TBD 🙂The text was updated successfully, but these errors were encountered: